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Journal Article

Charting Monosynaptic Connectivity Maps by Two-Color Light-Sheet Fluorescence Microscopy

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Niedworok,  Christian
Department of Molecular Neurobiology, Max Planck Institute for Medical Research, Max Planck Society;
Department of Biomedical Optics, Max Planck Institute for Medical Research, Max Planck Society;

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Schwarz,  Inna
Department of Molecular Neurobiology, Max Planck Institute for Medical Research, Max Planck Society;

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Ledderose,  Julia
Department of Molecular Neurobiology, Max Planck Institute for Medical Research, Max Planck Society;

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Giese,  Günter
Department of Biomedical Optics, Max Planck Institute for Medical Research, Max Planck Society;

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Schwarz,  Martin K.
Department of Molecular Neurobiology, Max Planck Institute for Medical Research, Max Planck Society;

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Citation

Niedworok, C., Schwarz, I., Ledderose, J., Giese, G., Conzelmann, K., & Schwarz, M. K. (2012). Charting Monosynaptic Connectivity Maps by Two-Color Light-Sheet Fluorescence Microscopy. Cell Reports, 2(5), 1375-1386. doi:10.1016/j.celrep.2012.10.008.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0024-0852-4
Abstract
Cellular resolution three−dimensional (3D) visualization of defined, fluorescently labeled long−range neuronal networks in the uncut adult mouse brain has been elusive. Here, a virus−based strategy is described that allowed fluorescent labeling of centrifugally projecting neuronal populations in the ventral forebrain and their directly, monosynaptically connected bulbar interneurons upon a single stereotaxic injection into select neuronal populations. Implementation of improved tissue clearing combined with light−sheet fluorescence microscopy permitted imaging of the resulting connectivity maps in a single whole−brain scan. Subsequent 3D reconstructions revealed the exact distribution of the diverse neuronal ensembles monosynaptically connected with distinct bulbar interneuron populations. Moreover, rehydratation of brains after light−sheet fluorescence imaging enabled the immunohistochemical identification of synaptically connected neurons. Thus, this study describes a method for identifying monosynaptic connectivity maps from distinct, virally labeled neuronal populations that helps in better understanding of information flow in neural systems